Advanced value of Sensor Data in Cycling through Machine Learning

通过机器学习实现传感器数据在骑行中的先进价值

• 批准号: 10074539
• 金额: $ 45.09万
• 依托单位: BODY ROCKET LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10074539
• 关键词: Advanced; value; Sensor; Data; Cycling

Body Rocket has delivered a game changing measurement system based on patented IP allowing cyclists and triathletes to measure aerodynamic drag to near wind tunnel accuracy on the bike under real-world road conditions, in real time, all the time. Since 80% of aerodynamic drag is due to your body (position, clothing, movement) there is much scope to improve all cyclists. We enable accurate aero measurement on the road instead of the artificially constrained and elite-only world of wind tunnels and velodromes.Our solution targets the competitive and mass market of tens-of-millions of performance-interested sports cyclists and triathletes globally. It adds aerodynamics insight to the already established demand for power measurement giving riders a more complete picture and actionable advice for performance improvement.This project focusses on the data analytics which will relate multiple interdependent measured parameters (e.g. vertical and horizontal forces, power output, weight distribution, wind, slope etc.) to impacts on aero performance thus enabling recommendations for improvement and optimisation during the ride. It will also design intuitive rider display/visualisation of key measures and advice on the bike computer. The project also investigates the use of the enormous proprietary data sets generated by our multi-sensor system to enable much better assumptions for a lower-cost 2-sensor system enabling additional exploitation options and even wider mass market accessibility.

Body Rocket提供了一个基于专利知识产权的改变游戏规则的测量系统，使自行车运动员和铁人三项运动员能够在真实的道路条件下，在真实的时间内，始终测量自行车上接近风洞精度的空气动力学阻力。由于80%的空气动力学阻力是由于你的身体（位置，服装，运动），有很大的空间，以改善所有骑自行车的人。我们能够在道路上进行精确的空气动力学测量，而不是在人为限制和精英专属的风洞和测速仪世界中进行测量。我们的解决方案面向全球数千万对性能感兴趣的运动自行车运动员和铁人三项运动员的竞争和大众市场。它为已经建立的动力测量需求增加了空气动力学洞察力，为车手提供更完整的画面和可操作的性能改进建议。该项目专注于数据分析，将多个相互依赖的测量参数（例如垂直和水平力，功率输出，重量分布，风，坡度等）联系起来。对空气动力学性能的影响，从而在乘坐过程中提出改进和优化建议。它还将在自行车计算机上设计直观的骑手显示/关键措施和建议的可视化。该项目还研究了如何使用我们的多传感器系统生成的大量专有数据集，以更好地假设成本更低的2传感器系统，从而实现更多的开发选项和更广泛的大众市场可及性。